Mark Cotton mcotton

How to install Tensorflow2 with GPU support in Ubuntu 20.04

Installation of Tensorflow2 with GPU support is easy and the only complication can be arisen from the CUDA compability which in turns depends on the Nvidia driver version. Before going farther, please check if your Nvidia Video Card is compatible with the required versions that are defined in this gist, use this link.

Tensorflow offers in its website a table of the compatibility between libraries for the target OS. You can visit that website in the following COMPATIBILITY TABLE that points to the Tensorflow installation from source for linux. For the time writing this gist, Tensorflow2 v2.5.0 requires CUDA v11.2 and CUDNN v8.2. It is really important to match the exact version, otherwise tensorflow will have problems loading the shared libraries as not finding the correct version.

CUDA version also requires for a minimum Nvidia driver version

Programming Achievements: How to Level Up as a Developer

This gist is part of a blog post. Check it out at:

http://jasonrudolph.com/blog/2011/08/09/programming-achievements-how-to-level-up-as-a-developer

	#!bin/bash

	mkdir /mnt/cdrom
	mount -r /dev/cdrom /mnt/cdrom
	cd /tmp
	tar zxf /mnt/cdrom/VMwareTools-*.tar.gz
	./vmware-tools-distrib/vmware-install.pl --default

	var app = require('../app');

	console.log();
	app.routes.all().forEach(function(route){
	console.log(' \033[90m%s \033[36m%s\033[0m', route.method.toUpperCase(), route.path);
	});
	console.log();
	process.exit();